Geospatial

AI/Machine Learning

Systems can learn from data, identify patterns and make decisions with minimal human intervention.

Big Data

Extremely large data sets can be analyzed computationally to reveal patterns, trends, and associations that can lead to valuable insights and better decisions.

01

Satellite Data

The bird's-eye view that satellites have allows them to see large areas of Earth at one time. This ability means satellites can collect more data at a faster rate than instruments on the ground.

Satellites are launching now at a rate of 100 per year, and this is expected to grow. New systems such as micro-satellites and open-data systems such as Sentinel and Landsat mean that new insights about both planetary systems and local level changes can now be achieved.

At HabitatSeven, we leverage satellite data in the production of data driven applications. This includes using observations to better understand water balance cycles and the impacts of extractive resources on surrounding environments, to help create predictive models for drought and forest fires.

02

Data Science

Data Science is the study of data. It utilizes methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data.

While ‘data science’ encompasses many things, our approach is focused on statistical analysis of large data sets to extract decision ready insights coupled with a distinct practice to ensure that algorithms are efficiently run to save on computation costs.

At HabitatSeven, our data science team has focused on developing algorithms to process data related to water delivery systems, evapotranspiration models, and climactic systems analysis.

03

Geospatial

Everything happens somewhere. Mapping and data applications that leverage geospatial technologies provide valuable insights at many scales, from local to global.

Geospatial data can come in many forms, from point based real-time data to gridded historical data products. Regardless of the form of the data, the application and development of geospatial systems depends on the size and scale of the data and must be implemented to maintain consistency and uptime.

At HabitatSeven, we use geospatial technologies to build mapping and graphing applications to help serve data for relevant geographies. This including delivering high resolution gridded climate data products, the visualization of data feeds using point based data, and using geospatial web systems as interface elements to access contextual information for specific geographic areas.

04

AI/Machine Learning

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves.

Machine learning can be applied to large scale environmental data sets to extract new knowledge about earth processes and the impacts that human are having on biodiversity, soil, and climate systems. This can also be applied specifically to identify changes in state. Coupled with earth observation data, machine learning holds the promise to provide better resource management guidance and more reliable mechanisms to understand human impacts on both the natural and built environment.

At HabitatSeven, our machine learning practice has been applied to better understanding field level agriculture systems, change states for resource management, and safety related threats connected to wildfire.

05

Big Data

Over 2.5 quintillion bytes of data are created every single day, and this number will only continue to grow. By 2020, it's estimated that 1.7MB of data will be created every second for every person on earth. Furthermore, new earth observation data systems are producing global scale data sets at unprecedented rates in terms of resolution, scope, and size.

As data generation is expected to continue to grow at exponential rates, extremely large data sets can be analyzed computationally to reveal patterns, trends, and associations that can lead to valuable insights and better decisions. It is the next logical step in computing as data is being generated and captured at exponentially higher rates every year.

At HabitatSeven, we build systems to process big data and deliver insights through intuitive, web-based interfaces. In this capacity, we have built systems to deliver earth observation data, global safety and health data, and data relevant to poverty alleviation.